Abstract
The smart electricity grids have been evolving to a more complex cyber-physical ecosystem of infrastructures with integrated communication networks, new carbon-free sources of power generation, advanced monitoring and control systems, and a myriad of emerging modern physical hardware technologies. With the unprecedented complexity and heterogeneity in dynamic smart grid networks comes additional vulnerability to emerging threats such as cyber attacks. Rapid development and deployment of advanced network monitoring and communication systems on one hand, and the growing interdependence of the electric power grids to a multitude of lifeline critical infrastructures on the other, calls for holistic defense strategies to safeguard the power grids against cyber adversaries. In order to improve the resilience of the power grid against adversarial attacks and cyber intrusions, advancements should be sought on detection techniques, protection plans, and mitigation practices in all electricity generation, transmission, and distribution sectors. This survey discusses such major directions and recent advancements from a lens of different detection techniques, equipment protection plans, and mitigation strategies to enhance the energy delivery infrastructure resilience and operational endurance against cyber attacks. This undertaking is essential since even modest improvements in resilience of the power grid against cyber threats could lead to sizeable monetary savings and an enriched overall social welfare.
Highlights
SMART GRIDS have transformed the monitoring, control, and operation of bulk power grids via modern communication, signal processing and control technologies
Fied complexity, heterogeneity and number of resources [4]. This is evidenced by the frequency, complexity, and severity of cyber attacks targeting several key power system operational functions such as automatic generation control (AGC), state estimation (SE), and energy management systems (EMS) which have been globally observed to be on the rise in recent years [5]
In [62], different machine learning classifying algorithms were tested in order to determine the viability of using machine learning as a decision support for system operators; the results demonstrated in Figure 9 show that it is a viable approach but more research is needed for deployment in an operational environment and practical settings
Summary
SMART GRIDS have transformed the monitoring, control, and operation of bulk power grids via modern communication, signal processing and control technologies. There have been reports that an experimental cyber attack was launched by researchers which caused a generator malfunction and self-destruct [14] Energy theft is another common cyber attack practice in which the electric power is misused or ‘‘stolen’’ by a malicious intruder. Characterization, modeling, and assessment of the power grid cyber vulnerability and designing solutions to protect the grid and enhance its resilience against cyber adversaries is essential This is because even modest improvements in resilience of the power grid against cyber threats (through advanced monitoring, efficient threat detection, and recovery algorithms) could lead to sizeable monetary savings and an enriched overall social welfare.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
